An novel data-driven structural optimisation method for engineering and science

Study level


Master of Philosophy


Vacation research experience scheme

Topic status

We're looking for students to study this topic.


Professor YuanTong Gu
Head of School, Mechanical, Medical and Process Engineering
Division / Faculty
Science and Engineering Faculty


Structural optimisation, an effective design method for light-weight and high-performance structures, traditionally relies on the computational mechanics method with empirical constitutive model of related material.

However, the empirical constitutive modelling remains an open question worldwide for a long term. The imperfect knowledge of constitutive laws and empiricism and arbitrariness of constitutive modelling process limit the applications of structural optimisation methods in advanced material structures.

Research activities

The project aims at developing a structural optimization method based on the data-driven computational mechanics, which bypasses the empirical modelling process and directly incorporates experimental data in calculations.

In this manner, the modelling empiricism, error and uncertainty are eliminated and loss of experimental information is thus avoided in structural optimization design.


This project will develop a novel structural optimisation method based on the data-driven computational mechanics. This will lead to a breakthrough in computer modelling method in engineering and science based on the recent development of big data technologies.


You may be able to apply for a research scholarship in our annual scholarship round.

Annual scholarship round



Contact the supervisor for more information.